Rerouting data of a streaming application

ABSTRACT

A streams manager monitors performance of a streaming application and determines if operators are underperforming according to a threshold. When the performance needs to be improved, the streams manager automatically modifies the flow graph to offload or reroute a stream of data, or part of a stream of data, to a similar operator to more efficiently utilize streaming resources. Operators are provided with multiple ports to allow the streams manager to send additional streams to the operator.

BACKGROUND 1. Technical Field

This disclosure generally relates to streaming applications, and morespecifically relates to rerouting a stream of data of an underperformingor overloaded operator to a compatible operator of another flow graph.

2. Background Art

Streaming applications are known in the art, and typically includemultiple operators coupled together in a flow graph that processstreaming data in near real-time. An operator typically takes instreaming data in the form of data tuples, operates on the tuples insome fashion, and outputs the processed tuples to the next operator.Streaming applications are becoming more common due to the highperformance that can be achieved from near real-time processing ofstreaming data.

Many streaming applications require significant computer resources, suchas processors and memory, to provide the desired near real-timeprocessing of data. However, the workload of a streaming application canvary greatly over time. Allocating on a permanent basis computerresources to a streaming application that would assure the streamingapplication would always function as desired (i.e., during peak demand)would mean many of those resources would sit idle when the streamingapplication is processing a workload significantly less than itsmaximum. Furthermore, what constitutes peak demand at one point in timecan be exceeded as the usage of the streaming application increases. Fora dedicated system that runs a streaming application, an increase indemand may require a corresponding increase in resources to meet thatdemand.

BRIEF SUMMARY

A streams manager monitors performance of a streaming application anddetermines if operators are underperforming according to a threshold.When the performance needs to be improved, the streams managerautomatically modifies the flow graph to offload or reroute a stream ofdata, or part of a stream of data, to a compatible operator to moreefficiently utilize streaming resources. Operators are provided withmultiple ports to allow the streams manager to send additional streamsto the operator.

The foregoing and other features and advantages will be apparent fromthe following more particular description, as illustrated in theaccompanying drawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

The disclosure will be described in conjunction with the appendeddrawings, where like designations denote like elements, and:

FIG. 1 is a block diagram of a cloud computing node;

FIG. 2 is a block diagram of a cloud computing environment;

FIG. 3 is a block diagram of abstraction model layers;

FIG. 4 is a block diagram showing an example of a streams manager thatoffloads a stream of data on an overloaded operator to a similaroperator of another flow graph as described herein;

FIG. 5 is a block diagram showing an operator of a streaming applicationaccording to the prior art;

FIG. 6 illustrates a block diagram of an operator with multiple ports asdescribed herein;

FIG. 7 illustrates a block diagram of a simplified example for reroutingdata of a streaming application to another operator;

FIG. 8 is a flow diagram of a method for a streams manager to redirectdata flow to another operator; and

FIG. 9 is a flow diagram of a specific method for step 830 in FIG. 8 fora streams manager to redirect stream flow to another operator.

DETAILED DESCRIPTION

The disclosure and claims herein relate to a streams manager thatmonitors performance of a streaming application and determines ifoperators are underperforming according to a threshold. When theperformance needs to be improved, the streams manager automaticallymodifies the flow graph to offload a stream of data, or part of a streamof data, to a compatible operator to more efficiently utilize streamingresources. Operators are provided with multiple ports to allow thestreams manager to send additional streams to the operator.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forloadbalancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a block diagram of an example of a cloudcomputing node is shown. Cloud computing node 100 is only one example ofa suitable cloud computing node and is not intended to suggest anylimitation as to the scope of use or functionality of embodiments of theinvention described herein. Regardless, cloud computing node 100 iscapable of being implemented and/or performing any of the functionalityset forth hereinabove.

In cloud computing node 100 there is a computer system/server 110, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 110 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, handheld or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 110 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 110 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 110 in cloud computing node100 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 110 may include, but are notlimited to, one or more processors or processing units 120, a systemmemory 130, and a bus 122 that couples various system componentsincluding system memory 130 to processor 120.

Bus 122 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnect (PCI) bus.

Computer system/server 110 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 110, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 130 can include computer system readable media in the formof volatile, such as random access memory (RAM) 134, and/or cache memory136. Computer system/server 110 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 140 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 122 by one or more datamedia interfaces. As will be further depicted and described below,memory 130 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions described in more detail below.

Program/utility 150, having a set (at least one) of program modules 152,may be stored in memory 130 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 152 generally carry out the functionsand/or methodologies of embodiments of the invention as describedherein.

Computer system/server 110 may also communicate with one or moreexternal devices 190 such as a keyboard, a pointing device, a display180, a disk drive, etc.; one or more devices that enable a user tointeract with computer system/server 110; and/or any devices (e.g.,network card, modem, etc.) that enable computer system/server 110 tocommunicate with one or more other computing devices. Such communicationcan occur via Input/Output (I/O) interfaces 170. Still yet, computersystem/server 110 can communicate with one or more networks such as alocal area network (LAN), a general wide area network (WAN), and/or apublic network (e.g., the Internet) via network adapter 160. Asdepicted, network adapter 160 communicates with the other components ofcomputer system/server 110 via bus 122. It should be understood thatalthough not shown, other hardware and/or software components could beused in conjunction with computer system/server 110. Examples, include,but are not limited to: microcode, device drivers, redundant processingunits, external disk drive arrays, RAID systems, tape drives, dataarchival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 200 isdepicted. As shown, cloud computing environment 200 comprises one ormore cloud computing nodes 100 with which local computing devices usedby cloud consumers, such as, for example, personal digital assistant(PDA) or cellular telephone 210A, desktop computer 210B, laptop computer210C, and/or automobile computer system 210N may communicate. Nodes 100may communicate with one another. They may be grouped (not shown)physically or virtually, in one or more networks, such as Private,Community, Public, or Hybrid clouds as described hereinabove, or acombination thereof. This allows cloud computing environment 200 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 210A-Nshown in FIG. 2 are intended to be illustrative only and that computingnodes 100 and cloud computing environment 200 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 200 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and the disclosure andclaims are not limited thereto. As depicted, the following layers andcorresponding functions are provided.

Hardware and software layer 310 includes hardware and softwarecomponents. Examples of hardware components include mainframes 352; RISC(Reduced Instruction Set Computer) architecture based servers 354;servers 356; blade servers 358; storage devices 360; and networks andnetworking components 362. In some embodiments, software componentsinclude network application server software 364 and database software366.

Virtualization layer 320 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers368; virtual storage 370; virtual networks 372, including virtualprivate networks; virtual applications and operating systems 374; andvirtual clients 376.

In one example, management layer 330 may provide the functions describedbelow. Resource provisioning 378 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 380provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 382 provides access to the cloud computing environment forconsumers and system administrators. Service level management 384provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 386 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA. The management layer further includes astreams manager (SM) 350 as described herein. While the SM 350 is shownin FIG. 3 to reside in the management layer 330, the SM 350 actually mayspan other levels such as the applications layer 340 shown in FIG. 3 asneeded.

Workloads layer 340 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 386; software development and lifecycle management 390;virtual classroom education delivery 392; data analytics processing 394;transaction processing 396 and mobile desktop 398.

As will be appreciated by one skilled in the art, aspects of thisdisclosure may be embodied as a system, method or computer programproduct. Accordingly, aspects may take the form of an entirely hardwareembodiment, an entirely software embodiment (including firmware,resident software, micro-code, etc.) or an embodiment combining softwareand hardware aspects that may all generally be referred to herein as a“circuit,” “module” or “system.” Furthermore, aspects of the presentinvention may take the form of a computer program product embodied inone or more computer readable medium(s) having computer readable programcode embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a non-transitory computer readable storage medium. A computerreadable storage medium may be, for example, but not limited to, anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device, or any suitable combinationof the foregoing. More specific examples (a non-exhaustive list) of thecomputer readable storage medium would include the following: anelectrical connection having one or more wires, a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM or Flashmemory), an optical fiber, a portable compact disc read-only memory(CD-ROM), an optical storage device, a magnetic storage device, or anysuitable combination of the foregoing. In the context of this document,a computer readable storage medium may be any tangible medium that cancontain, or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

FIG. 4 shows one suitable example of the streams manager 350 shown inFIG. 3. The streams manager 350 is software that manages one or morestreaming applications, including managing operators and data flowconnections between operators in a flow graph that represents astreaming application. The streams manager 350 includes a performancemonitor 410 with one or more performance thresholds 420. Performancethresholds 420 can include static thresholds, such as percentage used ofcurrent capacity or tuple rate, and can also include any suitableheuristic for measuring performance of a streaming application as awhole or for measuring performance of one or more operators in astreaming application. Performance thresholds 420 may include differentthresholds and metrics at the operator level, at the level of a group ofoperators, and/or at the level of the overall performance of thestreaming application. The stream performance monitor 410 monitorsperformance of a streaming application, and when current performancecompared to the one or more performance thresholds 420 indicates currentperformance needs to be improved, the stream performance monitor 410communicates with the streams manager 350 to attempt to improveperformance by rerouting streams to another operator as describedfurther below.

As discussed above, the streams manager 350 includes a performancemonitor 410 to monitor the performance of a streaming application andthe operators of the streaming application. The performance monitor 410determines when the performance of a streaming application can be andneeds to be improved and attempts to improve performance by reroutingstreams to another operator. Determining whether an operator isunderperforming may include tracking performance of the streamingapplication's operators. Performance can be determined in various ways.For example, an underperforming operator can be determined by comparingthe operator performance against historical data. Logs and other recordsof performance indicators from the same or similar operators can becollected and compared to the current performance. Performanceindicators could include for example: error rate, dropped tuple rate,response time, resource utilization, etc. Underperforming could also bedetermined by comparing the relative performance of the operators. Therelative performance could be determined by comparing to historicalpatterns or the percent of resources required by the differentoperators. Underperforming operators could also be determined bycomparing the performance of the operators to the performancethreshold(s) 420 in FIG. 4. A threshold range could also be set as anoptimal performance range for an operator and anything that is outsideof that range will trigger a response. If the performance is below therange the operator is underperforming. The performance range could be acombination of performance thresholds.

FIG. 5 is a block diagram 500 showing an operator 510 of a streamingapplication according to the prior art. Streaming applications typicallyinclude multiple operators coupled together in a flow graph that processstreaming data in near real-time. An operator typically takes instreaming data in the form of data tuples, operates on the tuples insome fashion, and outputs the processed tuples to the next operator oranother application. In this simple example, the operator 510 includesoperator logic 512. The operator logic 512 represents the function oroperation the operator 510 performs on input stream 514. Input stream514 is sent to the operator 510 on an input 516. After the input datastream is processed by the operator logic 512 the operator 510 outputsan output stream 518 on an output 520.

FIG. 6 illustrates a block diagram 600 of an operator 610 with multipleports as used and described herein. The operator 610 is similar to priorart operators in that it is also part of a streaming application thatprocess streaming data in near real-time to process data tuples andoutputs the processed tuples to the next operator. However, the operator610 is different from the prior art operators by providing multipleports, as shown in FIG. 6. In this simple example, the operator 610includes operator logic 612. The operator logic 612 represents thefunction or operation the operator 610 performs on one or more inputdata streams. In this simple example, data is input from two datastreams. Input stream1 614 is applied to input1 616 and stream2 618 isapplied to input2 620. Data tuples in stream1 614 and stream2 618 aresent to the operator 610 to be processed by the operator logic 612.After the input data streams are processed by the operator 610 theoperator 610 outputs stream1 as output_stream1 622 on output1 624 andoutputs stream2 as output_stream2 626 on output 2 628.

Again referring to FIG. 6, the operator 610 as described herein is asoftware application or a portion of a streaming software applicationthat processes streaming data in near real-time. The operator 610 isshown with two input ports 616, 620 as described above. The operator 610may be programmed and compiled to include multiple ports when it iscreated. The number of ports could be any number depending on thespecific application and is not limited to two ports as shown. The inputports may be initially unused at run time and then configured by thestreams manager to offload stream data as described herein by reroutingstream data to the newly configured input port of the operator. Theinput ports of the operator 610 may be similar to common communicationprotocol ports as used in the prior art. The operator 610 is programmedto process input streaming data that is placed on the input ports andplace a result on a corresponding output port. The streams managerreroutes a data stream by modifying the flow graph. This may includeconfiguring the various applications links or addressing to send data tothe unused input ports or ports of an operator that is determined to becompatible and has available input ports. The configuration to reroutedata streams may also include using internet protocol addressing tochange the destination of data tuples to the available operator input.

FIG. 7 illustrates a simplified example of rerouting data of a streamingapplication to another operator. A streaming application1 710 has threeoperators, operatorA 714, operatorB1 716, and operatorC 718. OperatorA714 originates a stream of tuples, which is processed by operatorB1 716and output to operatorC 718. The tuples from operatorA 714 are processedby logic (not shown) in operatorB 718 as described above. Similarly,another streaming application2 712 has three operators, operatorD 720,operatorB2 722, and operatorE 724. The streams manager 350 (FIG. 4)monitors performance of the streaming application1 710 to determine ifan operator is underperforming. In this example, we assume operatorB1716 is found to be underperforming according to one or more of thedefined thresholds as described in detail above. The streams manager inconjunction with the cloud manager then modifies the flow graph of thestreaming application to offload all or a portion of the stream to acompatible operator, in this case operatorB2 722 in application2 712. Asa result, application1 710 can utilize the resources of the physicalmachine or virtual machine hosting application2 712 to improve theoverall performance of streaming application1 710.

Again referring to FIG. 7, the streams manager 350 modifies the flowgraph of the streaming application1 710 to reroute all or a portion ofthe stream from operatorA 714 to operatorB1 716 to the compatibleoperatorB2 722. OperatorB2 722 has two input ports 730, 732. Havingdetermined that operatorB2 722 is compatible the streams managerdetermines that operatorB2 has an available input port 730 that is notbeing used. The streams manager may also check to determine ifoperatorB2 722 has sufficient capacity to handle the extra load fromoperatorB1 716 prior to rerouting. The streams manager then modifies theflow graph to send all or a portion of the output data from operatorA714 to operatorB2 722 by rerouting data 734 from operatorA 714 to theavailable input port 730. The streams manager also modifies the flowgraph to route the output data 736 from operatorB2 722 on output port738 to operatorC 718 which is the original destination for output datafrom operatorB1 716. The streams manager may determine an operator iscompatible in various ways. For example, the operators may be determinedto be compatible by looking at an operator signature similar to themethod used in object oriented programming. Further, the operators couldbe determined to be compatible because the two are each an instance of asingle class or program. Or they could be determined to be compatiblebased on a naming hierarchy or naming scheme where siblings in amulti-layer directory or naming structure are known to be compatibleoperators.

While operatorB2 722 is shown in FIG. 7 as an operator running in aseparate streaming application, operatorB2 could instead be an operatorthat is not part of a different application. For example, operatorB2 722could be a different operator in application1 710, or could be anoperator that has been created in a ready state but has not yetfunctioned as part of any application. The disclosure and claims hereinexpressly extend to offloading tuples to an operator that has multipleports, whether the operator is in a different streaming application ornot.

Referring to FIG. 8, a method 800 shows one suitable example forenhancing performance of a streaming application. Method 800 ispreferably performed by the streams manager 350. The streams managermonitors performance of the streaming application (step 810). Thestreams manager determines at least one operator in the flow graph thatis underperforming (step 820). The streams manager then offloads streamflow from the operator that is underperforming to another operator (step830). The method is then done.

FIG. 9 shows one suitable example of a method for a streams manager tooffload stream flow of an operator that is underperforming to anotheroperator. Method 900 thus shows a suitable method for performing step830 in method 800. The streams manager determines if there is acompatible operator that is sufficiently similar to the underperformingoperator with excess capacity (step 910). If there is no operatoravailable (step 920=no) then the method is done. If there is an operatoravailable (step 920=yes) then configure the flow graph to route data toan available input port of the available operator (step 930). Thestreams manager then configures the flow graph to route output data fromthe available operator on the corresponding output port to thedestination of the data in the original data flow (step 940). Then routeat least a portion of the data stream to the configured input port (step950). The method is then done.

The disclosure and claims herein relate to a streams manager thatmonitors performance of a streaming application on a physical or virtualmachine and determines if operators are underperforming according to athreshold. When the performance needs to be improved, the streamsmanager automatically modifies the flow graph to offload a stream ofdata, or part of a stream of data to a similar operator to moreefficiently utilize streaming resources.

One skilled in the art will appreciate that many variations are possiblewithin the scope of the claims. Thus, while the disclosure isparticularly shown and described above, it will be understood by thoseskilled in the art that these and other changes in form and details maybe made therein without departing from the spirit and scope of theclaims. For example, the cloud described herein could be a multi-cloudenvironment where the cloud manager is a multi-cloud manager such thatthe VMs provided to the streams manager are located on different clouds.

1. A computer-implemented method executed by at least one processor formanaging a streaming application, the method comprising: executing astreaming application that comprises a flow graph with a plurality ofoperators that process a plurality of data tuples; monitoringperformance of the streaming application; determining a first operatorin the flow graph that is underperforming; and offloading stream flow tothe first operator to a second operator comprising: determining thesecond operator has excess capacity and is compatible with theunderperforming first operator, wherein the second operator has a firstinput port that receives data from a second streaming application andfirst output port that outputs data to the second streaming application,wherein the second operator has a second input port; configuring toroute data from the streaming application to the second input port ofthe second operator; and configuring to route data from the secondoutput port of the second operator to the first streaming application.2. The method of claim 1 wherein the step of offloading stream flow tothe underperforming operator to the second operator further comprisesthe steps of: configuring to route data from an output port of thesecond operator; and routing at least a portion of the data stream tothe configured second input port.
 3. The method of claim 1 wherein thefirst operator is determined to be underperforming by comparing currentperformance of the plurality of operators of the streaming applicationto at least one defined performance threshold.
 4. The method of claim 1wherein the first operator of the streaming application is determined tobe underperforming by comparing the performance of the first operatoragainst historical data.
 5. The method of claim 4 wherein the historicaldata includes records of performance indicators from the same or similaroperators that are collected and compared to the current performance. 6.The method of claim 5 wherein where the performance indicators includeerror rate, response time, and resource utilization.
 7. The method ofclaim 1 wherein the streaming application is in a cloud environment.